Tunable phenotypic variability through an autoregulatory alternative sigma factor circuit

Abstract

Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σ V circuit in B. subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history, and genetic perturbations. Using single-cell time-lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σ V under lysozyme stress depends on stress level and on a memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma-anti-sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment.

VariableDNAtopology is an epigenetic generator of physiological heterogeneity in bacterial populations

“…Precise synchronization of these transcription patterns across every cell in the population is impossible, resulting in cell‐to‐cell variations in the outputs from copies of the same genes in different cells. Transcriptional activity is modulated not only by the genome‐wide distribution of RNA polymerase and the topoisomerases, but also by the actions of, inter alia, transcription factors, nucleoid‐associated proteins, sigma factors, intrinsic and extrinsic transcription terminators, and by the stalling and backtracking of RNA polymerase (Figueroa‐Bossi et al, 2022; Janissen et al, 2022; Schwall et al, 2021). This produces a population of cells exhibiting transcription patterns that are noisy and randomized (Urchueguía et al, 2021).…”

Hysteresis and noise floor in gene expression optimised for persistence against lethal events

“…Noisy gene expression constitutes a significant source of phenotypic variability within populations of genetically identical cells [1,2]. This heterogeneity arises from the inherent discreteness of transcription and/or translation reactions [3,4].…”

Activation domains can decouple the mean and noise of gene expression

“…One major consequence of bursty gene expression noise is its effect on cell fate decisions (Symmons and Raj, 2016;Bala ´zsi et al, 2011;Losick and Desplan, 2008;Bell et al, 2007), which are frequently determined by stochastic fluctuations in the levels of transcriptional regulators (Miller et al, 2008;Chang et al, 2008;Pina et al, 2012;Graf and Enver, 2009;Enver et al, 2009;Cross and Enver, 1997;Wolff et al, 2018;van Roon et al, 1989;Fiering et al, 1990;Dingemanse et al, 1994;Walters et al, 1995). Stochasticity in cell fate decisions represents a ''bet hedging'' strategy that keeps cellular phenotypes diverse, even in the absence of genetic or environmental variation (Rouzine et al, 2015;Singh and Weinberger, 2009;Weinberger et al, 2005Weinberger et al, , 2008Schwall et al, 2021;St-Pierre and Endy, 2008;Zeng et al, 2010;Golding, 2011;Dar et al, 2014;Razooky et al, 2015).…”